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Data Labelling Jobs in Virginia (NOW HIRING)

Manage the coordination and deployment of data tagging and labeling mechanisms across the DoW SAP enterprise. * Ensure compliance with DoW policies on data classification and information security ...

Data Scientist with 4 years of experience including experience in applied NLP, data labeling, entity or keyword extraction, and related topics. * Understanding of Weibull distribution and use for ...

Knowledge of information retrieval, embeddings, vector databases, semantic search, data labeling, classification models, model evaluation, and data quality assessment * Ability to translate military ...

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Data Labelling information

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

How much do data labelers get paid?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Some positions may offer project-based pay or bonuses for accuracy and efficiency.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and may be performed remotely or in a controlled environment.

How can I get started in data labeling?

To start in data labeling, gain familiarity with common tools like labeling software and understand data annotation standards. Building attention to detail and basic knowledge of the data types you will label, such as images or text, is essential. Many entry-level roles require no formal certification but may prefer candidates with basic computer skills and the ability to follow detailed instructions.
What are the most commonly searched types of Data Labelling jobs in Virginia? The most popular types of Data Labelling jobs in Virginia are:
What are popular job titles related to Data Labelling jobs in Virginia? For Data Labelling jobs in Virginia, the most frequently searched job titles are:
What cities in Virginia are hiring for Data Labelling jobs? Cities in Virginia with the most Data Labelling job openings:
Infographic showing various Data Labelling job openings in Virginia as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Geospatial AI Data Annotator

Enabled Intelligence

Falls Church, VA

Full-time

Re-posted 18 days ago


Job description

Geospatial AI Data Annotator

About Enabled Intelligence, Inc.

Enabled Intelligence, Inc. provides extremely accurate, precise and secure data labeling and AI solutions to help our government and commercial customers effectively deploy reliable and unbiased artificial intelligence technologies. We leverage the unique talents of veterans, people with different abilities, and subject matter experts to unlock the value of data to improve the delivery of public services and mission critical national security programs. Every Enabled solution starts with a team of highly-trained, US based data analysts that have both subject-matter expertise as well as a deep understanding of the best techniques and tools for AI data annotation, model development, and testing and evaluation.

At EI we respect and celebrate individuals from all walks of life. Our different backgrounds, cultures, experiences, and way of thinking make us stronger together and result in the most accurate and reliable AI solutions for our clients. We are extremely committed to a culture and environment where excellence can be achieved!

Geospatial AI Data Annotator

Data annotation is an essential component in training artificial intelligence/machine learning (AI/ML) algorithms. As a member of the Enabled Intelligence annotation team, you will help us collect and annotate unclassified, sensitive, and classified data for AI/ML technologies. We are looking for detail-oriented individuals who will collaborate with our team, label large amounts of data, and provide feedback to our data scientists and engineers to create high-quality labeled data sets. Joining our team means playing an integral role for the future of government AI/ML capabilities.

Responsibilities

  • Use advanced analytic tools to locate, label, tag and categorize various elements in large datasets
  • Interact with data science and data engineering teams to design new features for more efficient labeling techniques
  • Gain an in-depth knowledge of using both commercial and custom annotation software tools
  • Keep project manager informed of platform enhancement ideas, risks, and issues

Required Qualifications and Skills

  • Eligibility to obtain a Top Secret- SCI security clearance
  • US Citizenship Required
  • Ability to follow directions and meet deadlines
  • Ability to communicate reliably
  • Ability to learn and retain new information and apply it to a variety of projects
  • Ability to be a good team player and work with individuals with different communication, learning and working styles.
  • Ability to work independently including managing your schedule, attending all required meetings and completing projects within a deadline
  • Ability to understand and apply guidelines for data annotation
  • Ability to perform repetitive tasks while paying constant close attention to detail and delivery accurate and precise work
  • Ability to keep information confidential
  • Ability to work out of the Enabled Intelligence office located in Falls Church, VA Monday-Friday during normal business hours

Desired Qualifications and Skills

  • Previous experience working in a professional, office environment
  • Previous experience in an IT based position
  • Education background in information technology or technical field
  • Previous experience with data labeling or image annotation including analyzing 2D and 3D images, video, audio files, or unstructured text (EO, IR, SAR, FMV) 
  • Prior experience with business productivity tools like Microsoft Office, and/or Slack
  • Highschool Degree

Physical Requirements

  • Prolonged periods of sitting at a desk and working on a computer

Background Check & Security Clearance

  • Applicants selected will be subject to background investigation. Applicants must be eligible to receive a US security clearance at the secret level or higher which requires US Citizenship.